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DocLangID: Improving Few-Shot Training to Identify the Language of Historical Documents
In this work, we propose DocLangID, a transfer learning approach to identify the language of unlabeled historical documents.
Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data
One of the most pressing problems in the automated analysis of historical documents is the availability of annotated training data.
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